While certain key facts (the burglary itself, the link to the Committee to Re-Elect the President) were not in dispute, the critical question was the one being asked by Watergate Select Committee chairman Senator Sam Ervin of North Carolina: “What did the President know and when did he know it?” Now that tapes were available, that question could be settled definitely once and for all.

Watergate Special Prosecutor Archibald Cox filed a subpoena for eight of the tapes almost immediately, and for his trouble was fired in the Saturday Night Massacre. The backlash forced Nixon to appoint a new special prosecutor, Leon Jaworski, who continued to press for the tapes.

The Saturday Night Massacre took place on October 19, 1973. Just about a month later, on November 17, 1973, Richard Nixon traveled to Walt Disney World in Orlando, Florida, for a question and answer session before the 400 members of Associated Press Managing Editor’s Association.

As expected, the first questions involved the Watergate scandal and its consequences for the nation. The president of the Managing Editor’s Association wondered if Watergate was serious enough to take down the country.

“Mr. President,” he asked, “This morning, Governor Askew of Florida addressed this group and recalled the words of Benjamin Franklin. When leaving the Constitutional Convention he was asked, ‘What have you given us, sir, a monarch or a republic?’ Franklin answered, ‘A republic, sir, if you can keep it.’ Mr. President, in the prevailing pessimism of the lingering matter we call Watergate, can we keep that republic, sir, and how?” Nixon assured him that the Republic would continue.

The Louisville-Courier asked about two of the subpoenaed tapes that had gone missing. Nixon replied that he had other information — Dictaphone belts, diary notes, and telephone call recordings — that would substantiate his claims of innocence. The Rochester (New York) Democrat and Chronicle followed up, but gained no more information.

The Rochester Times-Union asked about the connection to the Ellsberg case, and Nixon replied that it was not part of Watergate, and should be considered a national security matter. The Detroit News followed with a softball question that allowed Nixon to once again reassure the public that everything was under control. The St. Petersburg Times asked about Nixon’s praise of Ehrlichman and Haldeman. Nixon replied, “First, I hold that both men and others who have been charged are guilty until I have evidence that they are not guilty.” (The president of the association later corrected Nixon, who agreed that he had misspoken.) The Des Moines Register and Tribune asked another question about the Ellsberg case, and Nixon reiterated his claim of national security.

Next, the subject of Nixon’s income tax returns came up. Nixon, according to the Providence Evening Bulletin, had paid only $792 in Federal income tax in 1970, and $878 in 1971. Nixon replied that he’d paid $79,000 in income tax in 1969, and the dramatic reduction in tax resulted from Nixon’s donation of his vice-presidential papers to the U.S. government, for which he’d taken a $500,000 deduction. (This practice was outlawed in 1969, so Nixon had gotten in just under the wire.)

The Tennessee Oak Ridger threw in another softball, asking Nixon if the demands of the Presidency were such that he just hadn’t had time to manage the re-election campaign directly. Nixon replied that yes, he’d taken a hands-off approach, but added “I say if mistakes are made, however, I am not blaming the people down below. The man at the top has got to take the heat for all of them.”

Before he took another question, however, Richard Nixon decided to go back to the question of his income tax payments. His government service had not been particularly lucrative, he said. “When I left office…you know what my net worth was? $47,000 total. Now, I have no complaints. In the next 8 years, I made a lot of money [from his book and law partnership]. And so, that is where the money came from.”

Even though the focus of the questions was on Watergate, it was the suspicion of financial irregularities in his personal life that seemed to concern Nixon most of all. Whatever anyone believed of him, his personal finances, he wanted to make clear, were completely aboveboard. It was in defending those finances that Richard Nixon made one of the most famous quotes of his lifetime:

“Let me just say this, and I want to say this to the television audience: I made my mistakes, but in all of my years of public life, I have never profited, never profited from public service--I have earned every cent. And in all of my years of public life, I have never obstructed justice. And I think, too, that I could say that in my years of public life, that I welcome this kind of examination, because people have got to know whether or not their President is a crook. Well, I am not a crook. I have earned everything I have got.” [Emphasis added.]

That seemed to stop the questions about Watergate. Reporters asked about the wiretapping of Richard Nixon’s brother Donald, additional matters of national security, the desirability of shield laws for reporters, executive privilege, the energy crisis, possible gas rationing, milk price supports, and what Nixon planned to do in retirement. (Hint: work for campaign finance reform.)

The event, televised live, went a few moments over the scheduled time, but that was okay in Nixon’s book. “It is a lousy movie anyway tonight.”

And when it was over, Richard Nixon said, “Well, thank you very much, gentlemen. I guess that is the end.”

Although I drove within feet of the killer and his fourth victim, I completely misread the situation. It was so inconceivable to me that a killing spree was taking place on a sunny Sunday afternoon in downtown Wheaton that I failed to process anything going on around me. I couldn’t have picked out the killer from a police lineup even though I saw him clearly. There was just enough askew about the situation that I decided for safety’s sake to drop by the police station on my way home — and it was there I learned that I had been an eyewitness to murder.

The incident itself quickly dropped off the front pages and has largely been lost to history. With the killer dead, there was no trial, and the number of victims was too small to register with the national media. The incident — and my failure — have stuck with me for many years, and armed with Google, I decided to find out what I could learn, and uploaded my blog piece on the 35th anniversary of the shootings.

For the record, and because it can’t be stated often enough, the victims were:

John L. Sligh, 43, of Rockville, Maryland: died.

Laureen D. Sligh, 40, his wife: wounded in both legs, survived.

Dr. Ralph C. Gomes, also of Rockville: minor injuries when his car crashed.

Harold S. Navy, Jr., 17, a freshman at the University of Maryland: wounded in the abdomen, but survived. Navy was the victim I saw.

Connie L. Stanley, 42, of Washington, DC: killed.

Rosalyn Stanley, 26, of Annapolis, Maryland: wounded.

Bryant Lamont Williams, 20, of Rockville: wounded.

The killer was Michael Edward Pearch, an unemployed carpenter living with his mother in Silver Spring, Maryland.

Since I first published the piece, I’ve heard from several other people connected to the incident.

About six months after “Eyewitness to Murder” appeared on my blog, I got an email from the daughter of John and Laureen Sligh. We exchanged emails and a few telephone calls, and finally arranged to have lunch on April 13, 2011, the 36th anniversary of the shooting. She told me her story. Her parents normally went to the movies on Sunday afternoon, and were just leaving the Wheaton Plaza theaters in separate cars when they encountered the shooter. The daughter herself was watching television when a special bulletin interrupted her show — and that’s how she learned her father was dead and her mother in the hospital. No one had bothered to sequester the news until the next of kin could be informed.

Both John and Laureen Sligh were scientists working for the Department of Defense. John Sligh was also a businessman and had purchased several small businesses. After his death, Laureen Sligh moved back to her home in Mississippi, and the businesses were left to the care of a relative who unfortunately was unable to keep them going, leaving the daughter without much in the way of means. We’ve kept in touch, and I’ve been pleased to hear that her daughters in turn are doing well; the youngest has ambitions to go to medical school.

I next heard from a man who was investigating the disappearance of the Lyon sisters, an unsolved case of two young girls who vanished in Wheaton in 1975. Although there’s no known direct connection between Pearch and the disappearance of the Lyon girls, Pearch’s killing spree makes him an obvious potential suspect.

An anonymous comment in June 2012 gave me some more information about Harold Navy, Jr. He wrote, “I'd just like to add a correction, if I may? I remember Harold Navy Jr, being shot in the upper leg and it affected his basketball playing as he had a long recouperation. I remember him returning to High School basketball after the shooting, so I don't think he was yet a freshman in college.”

In August, I heard from another eyewitness, who wrote, “I was in early elementary school at the time of this horrific crime. My family was in the Wheaton Pharmacy (now long gone, but it was in the shopping center with Planters Peanuts,etc.on Georgia Ave.). My memories are vague, but I do remember hearing the gun fire, hiding in the small bathroom with the wife of the owner, my mother and my brother while my father and the pharmacist grabbed heavy objects, ducked behind the counter and waited (seems silly in hindsight, but it was all they could do). I had supressed my memories until the sniper shootings several years ago. I was surprised that this crime never re surfaced in the media. We also found out after the attacks that as a white family, we most likely were safe, but there was no way to know that at the time.”

And finally, a little over a month ago, I heard from one more person — someone who had known the killer.

“My connection to this event is before the fact. I had met Mike Pearch a couple of years before the shooting and spent a lot of time with him camping over three days. With only one exception, our paths did not cross again for about two years, until I happened to randomly wind up doing yard work at his mother's house about 24 hours before the shooting began.

“Mike recognized me and came out of the house to talk. The conversation lasted about fifteen or twenty minutes and mostly covered the past two years. I know that there was much more behind his actions, but I have always been haunted by the question of whether something about that conversation may have been the final trigger for him to snap. I strongly suspect that the whole time he was speaking with me that he already had at least some idea about what he was going to do and perhaps he had already planned every detail.

“Not that I think it would have made much of a difference but I was never interviewed by the police. I don't think they ever knew much of anything about me or that I had just spoken to Mike. I was only fifteen at the time and could not figure out what to do with what I knew. My parents were even afraid to talk to me about it beyond being the ones to inform me about the shooting.

This whole episode is to me like a manila file folder that has no place in the file cabinet. I try to put it somewhere; maybe in the wrong drawer, maybe in the trash, maybe I try to bury it under other things but sooner or later it keeps reappearing on top of the file cabinet. I suspect you and others, connected to this event, feel the same way. And always the question, ‘Is there anything I could have done?’

Obviously, there is not a thing I can do to change the past but if there is any way that sharing what I know can bring some relief to someone else affected by this tragedy then perhaps I could finally put this in the file cabinet under, ‘Something good finally came out of that part of my life.’”

For the story of how we met, and what I’ve learned since then, stay tuned.

Friday, November 2, 2012

While famous malapropist Yogi Berra is most often cited for the quote, “Prediction is very difficult, especially about the future,” it appears that the source was actually Danish physicist and Nobel Prize laureate Niels Bohr. Bohr, whose pioneering work in quantum physics would naturally equip him with a keen sense of the limits of knowledge, also had a sense of humor. (He also said, “An expert is a man who has made all the mistakes that can be made in a very narrow field.”)

Bias and Accuracy

In my long study of cognitive biases on this blog and in my compilation Random Jottings 6: The Cognitive Biases Issue, I was struck again and again by how many of the biases had to do with perceptions of probability. From ambiguity aversion to the base rate fallacy to the twin problems of the gambler’s fallacy and the ludic fallacy, we have repeatedly shown ourselves to be incapable of judging probabilities with any degree of precision or understanding. When people rate their own decisions as "95% certain," research shows they're wrong approximately 40% of the time.

With the 2012 presidential election only four days away as I write this, the issue of prediction and forecasting is uppermost in the minds of every partisan and pundit. Who will win, and by how much? Checking the polls as I write, the RealClearPolitics average gives President Obama a 0.1% lead over Governor Romney (47.4% to 47.3%). Rasmussen has Romney up by 2 (49% to 47%), Gallup by 5 (51% to 46%), and NPR by 1 (48% to 47%). On the other hand, ABC/Wash Post and CBS/NY Times both have Obama leading by 1 (49% - 48% for ABC, 48% - 47% for CBS), and the National Journal has Obama up by 5 (50% - 45%). No matter what your politics, you can find polls to encourage you and polls to discourage you about the fate of your preferred candidate.

Some polls normally come with qualifications. Rasmussen traditionally leans Republican; PPP often skews Democratic. That doesn't means either poll is irrelevant or useless. Accuracy and bias are two different things. Bias is the degree to which a poll or sample leans in a certain direction. If a study comparing Rasmussen or PPP polls to the actual election results shows that Rasmussen's results tend to be 2% more toward the Republican candidate (or vice versa for PPP), both polls are quite useful — you just have to adjust for the historical bias. If on the other hand a poll overestimates the Democratic vote by 10% in one election and then overestimates the Republican vote by 10% in another election, there's no consistent bias, but the poll's accuracy is quite low. In other words, a biased poll can be a lot more valuable than an inaccurate one.

Selection Bias

Of course, political polls (or polls of any sort) are subject to all sorts of error. My cognitive biases entry on selection bias summarizes common concerns. For instance, there’s a growing argument that land-line telephone polls, once the gold standard of scientific opinion surveys, are becoming less reliable. Cell phone users are more common and skew toward a different demographic. There's also a sense that people are over-polled. More and more people are refusing to participate, meaning that the actual sample becomes to some extent self-selected: a random sample of people who like to take polls. People who don’t like to take polls are underrepresented in the results, and there’s no guarantee that class feels the same as the class answering. (I myself usually hang up on pollsters, and I've often thought it might help our political process if we agreed to lie to pollsters at every opportunity.)

Selection bias can happen in any scientific study requiring a statistical sample that is representative of some larger population: if the selection is flawed, and if other statistical analysis does not correct for the skew, the conclusions are not reliable.

Time interval bias. Error resulting from a flawed selection of the time interval. Examples include starting on an unusually low year and ending on an unusually high one, terminating a trial early when its results support your desired conclusion or favoring larger or shorter intervals in measuring change.

Exposure bias. Error resulting from amplifying trends. When one disease predisposes someone for a second disease, the treatment for the first disease can appear correlated with the appearance of the second disease. An effective but not perfect treatment given to people at high risk of getting a particular disease could potentially result in the appearance of the treatment causing the disease, since the high-risk population would naturally include a higher number of people who got the treatment and the disease.

Data bias. Rejection of “bad” data on arbitrary grounds, ignoring or discounting outliers, partitioning data with knowledge of the partitions, then analyzing them with tests designed for blindly chosen ones.

Studies bias. Earlier, we looked at publication bias, the tendency to publish studies with positive results and ignore ones with negative results. If you put together a meta-analysis without correcting for publication bias, you’ve got a studies bias. Or you can perform repeated experiments and report only the favorable results, classifying the others as calibration tests or preliminary studies.

Attrition bias. A selection bias resulting from people dropping out of a study over time. If you study the effectiveness of a weight loss program only by measuring outcomes for people who complete the whole program, it’ll often look very effective indeed — but it ignores the potentially vast number of people who tried and gave up.

Unskewing the Polls

In general, you can’t overcome a selection biases with statistical analysis of existing data alone. Informal workarounds examine correlations between background variables and a treatment indicator, but what’s missing is the correlation between unobserved determinants of the outcome and unobserved determinants of selection into the sample that create the bias. What you don’t see doesn’t have to be identical to what you do see. That doesn't stop people from trying, however.

With that in mind, the website unskewedpolls.com, developed by Dean Chambers, a Virginia Republican, attempts to correct what he sees as a systematic bias as to the proportion of Republicans and Democrats in the electorate. By adjusting poll results that in Chambers’ view are oversampling Democrats, he concludes (as of today) that Romney leads Obama nationally by 52% - 47%, a five point lead, and that Romney also leads in enough swing states that Chambers projects a Romney landslide in the electoral college of 359 to 179, with 270 needed for victory.

Chambers argues that other pollsters and analysts who show an edge for Obama are living in a “fantasy world.” In particular, he trains his disgust on Nate Silver, who writes the blog FiveThirtyEight on the New York Times website, describing him as “… a man of very small stature, a thin and effeminate man with a soft-sounding voice that sounds almost exactly like the ‘Mr. New Castrati’ voice used by Rush Limbaugh on his program. In fact, Silver could easily be the poster child for the New Castrati in both image and sound. Nate Silver, like most liberal and leftist celebrities and favorites, might be of average intelligence but is surely not the genius he's made out to be. His political analyses are average at best and his projections, at least this year, are extremely biased in favor of the Democrats.” (You may notice a little bit of ad hominem here. Clearly a short person with an effeminate voice can’t be trusted.)

A quick review of the types of selection bias above will identify several problems with the unskewed poll method. Indeed, it's hard to find anyone not wedded to the extreme right who's willing to endorse Chambers' methodology. The approach is bad statistics, and would be equally bad if done on behalf of the Democratic candidate.

Nate Silver and FiveThirtyEight

Other views of Nate Silver are a bit more positive. Silver first came to prominence as a baseball analyst, developing the PECOTA system for forecasting performance and career development of Major League Baseball players, then won some $400,000 using his statistical insights to play online poker. Starting in 2007, he turned his analytical approach to the upcoming 2008 election, and predicted the winner of 49 out of 50 states. This resulted in his being named one of the world’s 100 most influential people by Time magazine, and his blog was picked up by the New York Times. (He's also got a new book out, The Signal and the Noise: Why So Many Predictions Fail — But Some Don't. I recommend it.)

As of today, Nate Silver’s predictions on FiveThirtyEight differ dramatically from the UnSkewedPolls average. Silver predicts that Obama will take the national popular vote 50.5% to 48.4%, and the electoral college by 303 to 235. One big difference between Dean Chambers and Nate Silver is that Chambers is certain, and Silver is not. He currently gives Obama an 80.9% chance of winning, which means that Silver gives Romney a 19.1% chance of victory using the same data.

This 80% - 20% split is known to statisticians as a confidence interval, a measure of the reliability of an estimate. In other words, Silver knows that the future is best described as a range of probabilities. Neither he, nor Chambers, nor you, nor I “know” the outcome of the election that will take place next Tuesday, and we will not “know” until the votes have been counted and certified (and any legal challenges resolved).

Predictions vs. Knowledge

In other words, when we predict, we do not know.

Keeping the distinction straight is vital for anyone whose job includes the need to forecast what will happen. Lawyers don’t “know” the outcome of a case until the jury or judge renders a verdict and the appeals have all been resolved. Risk managers don’t “know” whether a given risk will occur until we’re past the point at which it could possibly happen. Actuaries don’t “know” how many car accidents will take place next year until next year is over and the accidents have been counted. But lawyers, risk managers, actuaries — and pollsters — all predict nonetheless.

A statistical prediction, by its very nature, contains uncertainty and should therefore be expressed in terms of the degree of confidence that the forecaster has determined. “The sun’ll come out tomorrow,” sings Annie in the eponymous musical, and she’s almost certainly right. But that’s a prediction, not a fact. While the chance of the Sun going nova are vanishingly small, they aren’t exactly zero.

Confidence Level and Margin of Error

Poll results usually report both a confidence level and a range of error, such as “95% confidence with an error of ±3%.” The error rate is the uncertainty of the measurement itself. If we flip a coin 100 times, the theoretical probability is 50 heads and 50 tails, but if it came out 53 heads and 47 tails (or vice versa), no one would be surprised. That’s equivalent to an error of ±3%. In other words, a small wobble in the final number should come as a shock to no one.

The confidence level, on the other hand, is the degree of confidence you have that your final number will stay within the error range. The probability that an honest coin flipped 100 times would produce 70 heads and 30 tails is low, but it’s within the realm of possibility. In other words, the “95% confidence” measurement tells us that 95% of the time, the actual result should be within the margin of error — but that 5% of the time, it will fall outside the range. (There’s a bit of math that goes into measuring this, but it's outside the scope of this piece.)

Winning at Monte Carlo

Nate Silver’s 80% confidence number comes from using a modeling technique known as a Monte Carlo simulation, which is also used in project management as a modern and superior alternative to the old PERT calculation, a weighted average of optimistic, pessimistic, and most likely outcomes. In a Monte Carlo simulation, a computer model runs a problem over and over again in thousands of iterations, choosing random numbers from within the specified ranges, and then calculates the result. If the polls are right 95% of the time within a ±3% margin of error, the program chooses a random number within the error range 95% of the time, and 5% of the time chooses a number outside the range, representing the probability that the polls could be all wet. In running five or ten thousand simulations, the results gave the victory to Obama 80.9% of the time, and to Romney 19.1% of the time.

Tomorrow, the answer may be different. Silver will enter new data, and the computer will run five or ten thousand more simulations. Each day, the probability of winning or losing will change slightly, until the final results are in and the answer is no longer a matter of probability but a matter of fact.

The Thrill of Victory and the Agony of Defeat

Astute readers may notice the parallels here to Schrödinger's Cat, which is mathematically both alive and dead until the box is opened. Personally, I put a lot of credence into Silver’s analysis; his approach is in line with my understanding of statistics. That means I think Obama is very likely to win next Tuesday — but only within a range of probability.

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Michael Dobson

About Me

Michael Dobson is the author of over 60 books on leadership, project management, fiction, and history. A former researcher at the Smithsonian Institution and head of game design for TSR, Inc., Dobson's wide-ranging interests include science, science fiction, history, and much more.

THE STORY OF A SPECIAL DAY: What happened on your birthday? In this series of (eventually) 366 books, learn the true story about every day of the year! Click the link to read more about it — and visit Dobson's Improbable History every day for the latest on this day in history!